With the gradual maturity of the automatic train operation (ATO) system in subways, its application scope has also expanded to the high-speed railway field. Considering that the ATO system is still in the early stages of operation, it will take time to fully mature, and definite specifications of the requirements for system operation have not yet been formed. This paper presents the operational design domain (ODD) of the high-speed railway ATO system and proposes a scenario analysis method based on the operational design domain to obtain the input conditions of the system requirements. The article models and verifies the scenario of the linkage control of the door and platform door based on the UPPAAL tools and extracts the input and expected output of the system requirements of the vehicle ATO system. Combined with the input conditions of the system requirements, the system requirements of the vehicle ATO in this scenario are finally obtained, which provides a reference for future functional specification generation and test case generation.

In high-speed railway signaling systems, the network structure of the Train Control Center and Inter-locking Integrated System (TIS) is highly complex, with a large number of interfaces, numerous redundant channels, and forwarding components such as switches. These factors result in challenges such as insufficient accuracy, low efficiency, and poor real-time performance in terms of network monitoring and fault diagnosis. As the scale of railway yards continues to expand, these issues are becoming increasingly prominent. To address these challenges, this paper proposes a network fault propagation model based on the Fuzzy Broad Learning System (FBLS). By leveraging nonlinear transformations and feature mapping techniques, FBLS can efficiently extract and analyze network fault features, even with a relatively small amount of data. Experimental results show that the FBLS-based diagnostic model achieves higher accuracy and faster response speed in fault identification and propagation path analysis compared to traditional graph theory and fuzzy reasoning methods. Further comparisons with existing methods validate the advantages of FBLS in handling multi-source data, improving noise tolerance, and adapting to large-scale railway yard network systems, demonstrating its broad application prospects in railway signaling systems.

At present, the construction of high-speed railway in the western region has become one of the key points in China. However, the existing train control systems do not adapt to the environment. So a new type of train control system (TCS-NT) is proposed. However, for TCS-NT, the definition and content of its operating scenarios are not clear, and the construction of operating scenarios is mostly involves subjective analysis. It faces problems such as a lack of a comprehensive operating environment analysis method, a method for selecting scenario elements for varying test requirements, and inexplicable design choices. In this paper, the Operational Design Domain (ODD) and a key element extraction method for simulation scenarios are proposed to analyze the operational environment of the TCS-NT. Using this method, the impact of each scenario element on the sub-functions is sequentially analyzed in the tracking operation scenario of the TCS-NT. According to the influence on each sub-function, a mapping equation is constructed for the three-dimensional plane comprising element, structure, and function, and scenario elements are extracted using the discriminant matrix. In this paper, the method is used to analyze the operation scenario in the train tracking scene, and the feasibility of the method is verified.

With the continuous growth of high‐speed railway passenger transportation demand, how to improve the capacity has become an urgent problem to be solved. The signal system based on moving block can effectively improve the utilization of line capacity. From the perspective of signal system, this paper studies the line capacity benefits brought by CTCS‐3 combined with moving block. First, in response to the challenges of implementing moving block under CTCS‐4 based on existing technologies and considering the need for line interconnection, this paper proposes a CTCS‐3 solution that combined moving block. Secondly, this paper proposes a multiagent‐based high‐speed railway network train tracking simulation modeling method and establishes infrastructure and train simulation models under two signal system scenarios: CTCS‐3 and CTCS‐3 combined with moving block. Finally, this paper selects the Beijing‐Shanghai High‐Speed Railway as a research case and verifies the railway capacity indicators. The results show that the application of CTCS‐3 combined with moving block is expected to further tap the transportation capacity potential of the existing high‐speed railway network.